As shown in FIG. 1, image retargeting adapts a large image 110 to a small image 120 so that significant objects in the large image are still recognizable in the small image. Image retargeting can be for used for devices with a small display screen, such as mobile telephones and PDAs. Image retargeting can also be used to generate ‘thumbnails’ of a large number of images to facilitate image browsing.
As shown in FIG. 1, known methods typically use linear scaling 101 or cropping 102. Scaling makes object too small to be recognized, while cropping eliminates objects entirely, see United States Patent Application 20050007382, Alexander K. Schowtka, filed Jan. 13, 2005, “Automated image resizing and cropping.”
Most methods simply scale large images to a smaller size. If a specific portion of the large image is significant, or a change in the aspect ratio would cause distortion, cropping can be used with scaling.
Some methods do image retargeting automatically, see Suh et al., “Automatic thumbnail cropping and its effectiveness,” Proceedings of the 16th annual ACM symposium on User interface software and technology, ACM, pp. 11-99, 2003; and Chen et al., “A visual attention model for adapting images on small displays,” ACM Multimedia Systems Journal, pp. 353-364, 2003. Those methods use an importance model to identify significant portions in large images. Those methods can be extended to videos. However, cropping is of little use when there are multiple significant portions 130 spread over the image, see FIG. 1.
Another method uses a spline-based process for enlarging or reducing images with arbitrary scaling factors, Munoz, “Least-squares image resizing using finite differences,” IEEE Transactions on Image Processing 10, 9, pp. 1365-1378, Sep. 2001. Their method applies a least-squares approximation of oblique and orthogonal projections for splines.
Another method renders small portions of a large image serially, Chen et al., “A visual attention model for adapting images on small displays,”Tech. Rep. MSRTR-2002-125, Microsoft Research, Nov. 2002. It is also possible to make a ‘tour’ of the large image by scanning it piecemeal, Liu et al., “Automatic browsing of large pictures on mobile devices,” Proceedings of the eleventh ACM international conference on Multimedia, ACM, pp. 148-155, 2003.
Other methods deform the large image to exaggerate portions of image. For a survey, see Carpendale et al., “A framework for unifying presentation space,” Proceedings of UIST '01, pp. 82-92, 2001.